762 programming-"https:"-"Inserm"-"FEMTO-ST"-"https:"-"https:"-"https:"-"https:" positions at Nature Careers
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risk, tumor formation, and impacts on cancer treatment for patients with hereditary predisposition to cancer. This one-year program provides fellows with advanced training in cancer genetics as
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studying neural circuits Familiarity with programming languages (e.g. R, Python) and an ability to work with large datasets Strong record of peer-reviewed publications Ability to independently design and
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intense mutual collaboration Salary according to tariff agreement, extra annual payment, and company pension plan (VBL) A respectful and appreciative work environment within a diverse team For inquiries
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to tariff agreement, extra annual payment, and company pension plan (VBL) 30 days of vacation per year, plus two additional days off on Christmas Eve and New Year's Eve Career development in a
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simulation models Programming skills (e.g. Matlab or Python) Willingness to supervise young scientists Enthusiasm and enjoyment of working independently on developing fresh ideas and solutions Good
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neuronal differentiation (preferred)Experience with cellular phenotyping, including lysosomal and/or mitochondrial profiling (advantage)Programming skills in R and/or PythonFamiliarity with bioinformatic
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opportunities for everyone: We look forward to diverse personalities in the team! How to apply: Application documents should include: letter of motivation including time plan for doctoral thesis milestones
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degree with 0-2 years experience) in Bioinformatics, Computational Biology, or a related field. Experience in at least one programming language (Python preferred) and statistical package (R
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-research program with application to diverse groups of childhood catastrophic illness. The position can be filled at the Assistant, Associate or Full faculty level and can be within the Clinician-Scientist
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cultivation plan generation, pest/disease Q&A, market forecast, policy impact analysis. Create an open platform for agricultural large models: supporting plugin invocation, LoRA/QLoRA fine-tuning, federated